code: def test_llava_merge_inputs_error_bug(self):
      # This is a reproducer of https://github.com/huggingface/transformers/pull/28333 and makes sure it does not happen anymore
      model_id = "llava-hf/llava-1.5-7b-hf"
      model = LlavaForConditionalGeneration.from_pretrained(
          model_id, torch_dtype=torch.float16, low_cpu_mem_usage=True
      ).to(torch_device)
  
      # Simulate some user inputs
      pixel_values = torch.randn(
          (2, 3, 336, 336),
          dtype=torch.float,
          device=torch_device,
      )
      input_ids = torch.tensor(
          [
              [32001, 32001, 1, 15043, 7084, 32000, 29871, 13, 7900],
              [1, 15043, 7084, 29901, 29871, 32000, 29871, 13, 7900],
          ],
          dtype=torch.long,
          device=torch_device,
      )
      attention_mask = torch.tensor(
          [[0, 0, 1, 1, 1, 1, 1, 1, 1], [1, 1, 1, 1, 1, 1, 1, 1, 1]],
          dtype=torch.long,
          device=torch_device,
      )
  
      # Make sure that the loss is properly computed
      loss = model(
          pixel_values=pixel_values,
          input_ids=input_ids,
          attention_mask=attention_mask,
          labels=input_ids,
      ).loss
      loss.backward()
  
imports: import gc
  import unittest
  import requests
  from transformers import AutoProcessor, LlavaConfig, LlavaForConditionalGeneration, is_torch_available, is_vision_available
  from transformers.testing_utils import require_bitsandbytes, require_torch, require_torch_gpu, slow, torch_device
  from ...test_configuration_common import ConfigTester
  from ...test_modeling_common import ModelTesterMixin, floats_tensor, ids_tensor
label_desc: Use image node_id 9 for calling the LlavaForConditionalGenerationIntegrationTest obj's underlying member method code with example usage: obj.test_llava_merge_inputs_error_bug() without return types